Abstract: In the current landscape, addressing missing values poses a significant challenge when dealing with real-world problems. In this work, a hybrid model, DT-GA-FLANN, is proposed to address the ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Cities are increasingly becoming the epicenter of climate-related risks, with research showing that impervious surfaces (e.g.

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...

A practical guide to navigating AI risk, readiness, and use case adoption KNOXVILLE, TN, UNITED STATES, January 15, ...

Abstract: This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is ...

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1 School of Nursing, Naval Medical University, Shanghai, China 2 Department of Clinical Psychology, Chongqing Mental Health Center, Chongqing, Shanghai, China Background: Benefit finding (BF) improves ...

This project explores two different investigation using methods of machine learning and hybrid approach to predict the peak energy consumption in Ireland and energy production in Portugal based on ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...